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Two decades ago, Saul Perlmutter, Brian Schmidt, and Adam Reiss shocked the world when they published research showing not only that the Universe was expanding, but that the expansion was occurring at an accelerating rate. The discovery came as a complete surprise even to the astronomers themselves, and netted them a Nobel Prize in 2011.

Textbook descriptions of brain cells make neurons look simple: a long spine-like central axon with branching dendrites. Taken individually, these might be easy to identify and map, but in an actual brain, they're more like a knotty pile of octopi, with hundreds of limbs intertwined. This makes understanding how they behave and interact a major challenge for neuroscientists.

If you wanted to deliver a package across the street and avoid being hit by a car, you could program a powerful computer to do it, equipped with sensors and hardware capable of running multiple differential equations to track the movement and speed of each car. But a young child would be capable of doing the same task with little effort, says Alex Demkov, professor of physics at The University of Texas at Austin.

Advances in machine learning are announced every day, but efforts to fundamentally rethink the core algorithms of AI are rare.

Last year, scientists demonstrated that twisted bilayer graphene — a material made of two atom-thin sheets of carbon with a slight twist — can exhibit alternating superconducting and insulating regions. Now, a new study in the journal Nature by scientists from Spain, the U.S., China and Japan shows that superconductivity can be turned on or off with a small voltage change, increasing its usefulness for electronic devices.